Multiple Linear Regression - Estimated Regression Equation
Rate[t] = + 3.65 + 0.15StatusDummy[t] + 4.45CurryDummy[t] -4.1Interaction[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)+3.65 0.3365+1.0850e+01 4.244e-17 2.122e-17
StatusDummy+0.15 0.4759+3.1520e-01 0.7535 0.3767
CurryDummy+4.45 0.4759+9.3510e+00 2.842e-14 1.421e-14
Interaction-4.1 0.673-6.0920e+00 4.248e-08 2.124e-08


Multiple Linear Regression - Regression Statistics
Multiple R 0.7823
R-squared 0.612
Adjusted R-squared 0.5967
F-TEST (value) 39.96
F-TEST (DF numerator)3
F-TEST (DF denominator)76
p-value 1.332e-15
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 1.505
Sum Squared Residuals 172.1


Menu of Residual Diagnostics
DescriptionLink
HistogramCompute
Central TendencyCompute
QQ PlotCompute
Kernel Density PlotCompute
Skewness/Kurtosis TestCompute
Skewness-Kurtosis PlotCompute
Harrell-Davis PlotCompute
Bootstrap Plot -- Central TendencyCompute
Blocked Bootstrap Plot -- Central TendencyCompute
(Partial) Autocorrelation PlotCompute
Spectral AnalysisCompute
Tukey lambda PPCC PlotCompute
Box-Cox Normality PlotCompute
Summary StatisticsCompute


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast		Residuals
Prediction Error
1 4 4.15-0.15
2 5 4.15 0.85
3 3 4.15-1.15
4 4 4.15-0.15
5 5 4.15 0.85
6 3 4.15-1.15
7 7 4.15 2.85
8 5 4.15 0.85
9 6 4.15 1.85
10 3 4.15-1.15
11 2 4.15-2.15
12 4 4.15-0.15
13 5 4.15 0.85
14 2 4.15-2.15
15 3 4.15-1.15
16 6 4.15 1.85
17 4 4.15-0.15
18 4 4.15-0.15
19 6 4.15 1.85
20 2 4.15-2.15
21 3 3.8-0.8
22 5 3.8 1.2
23 4 3.8 0.2
24 2 3.8-1.8
25 7 3.8 3.2
26 1 3.8-2.8
27 4 3.8 0.2
28 4 3.8 0.2
29 7 3.8 3.2
30 4 3.8 0.2
31 3 3.8-0.8
32 3 3.8-0.8
33 3 3.8-0.8
34 3 3.8-0.8
35 2 3.8-1.8
36 5 3.8 1.2
37 5 3.8 1.2
38 3 3.8-0.8
39 6 3.8 2.2
40 2 3.8-1.8
41 8 8.1-0.1
42 9 8.1 0.9
43 10 8.1 1.9
44 7 8.1-1.1
45 8 8.1-0.1
46 9 8.1 0.9
47 10 8.1 1.9
48 6 8.1-2.1
49 6 8.1-2.1
50 7 8.1-1.1
51 8 8.1-0.1
52 9 8.1 0.9
53 8 8.1-0.1
54 7 8.1-1.1
55 5 8.1-3.1
56 11 8.1 2.9
57 7 8.1-1.1
58 8 8.1-0.1
59 10 8.1 1.9
60 9 8.1 0.9
61 3 3.65-0.65
62 5 3.65 1.35
63 4 3.65 0.35
64 2 3.65-1.65
65 6 3.65 2.35
66 1 3.65-2.65
67 4 3.65 0.35
68 4 3.65 0.35
69 5 3.65 1.35
70 4 3.65 0.35
71 3 3.65-0.65
72 3 3.65-0.65
73 4 3.65 0.35
74 3 3.65-0.65
75 2 3.65-1.65
76 5 3.65 1.35
77 4 3.65 0.35
78 3 3.65-0.65
79 6 3.65 2.35
80 2 3.65-1.65


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
7 0.8225 0.3549 0.1775
8 0.7163 0.5673 0.2837
9 0.6907 0.6187 0.3093
10 0.6749 0.6502 0.3251
11 0.77 0.46 0.23
12 0.681 0.638 0.319
13 0.6057 0.7886 0.3943
14 0.685 0.63 0.315
15 0.641 0.718 0.359
16 0.6695 0.661 0.3305
17 0.5863 0.8273 0.4137
18 0.5009 0.9982 0.4991
19 0.5611 0.8779 0.4389
20 0.604 0.792 0.396
21 0.5301 0.9399 0.4699
22 0.5112 0.9775 0.4888
23 0.4343 0.8686 0.5657
24 0.4557 0.9115 0.5443
25 0.6778 0.6444 0.3222
26 0.8083 0.3834 0.1917
27 0.7571 0.4859 0.2429
28 0.6994 0.6013 0.3006
29 0.8532 0.2935 0.1468
30 0.8115 0.3769 0.1885
31 0.7771 0.4458 0.2229
32 0.7378 0.5244 0.2622
33 0.6946 0.6108 0.3054
34 0.6488 0.7024 0.3512
35 0.6746 0.6509 0.3254
36 0.6445 0.7111 0.3555
37 0.6174 0.7653 0.3826
38 0.5694 0.8611 0.4306
39 0.674 0.652 0.326
40 0.6536 0.6927 0.3464
41 0.5897 0.8206 0.4103
42 0.542 0.9159 0.458
43 0.5548 0.8905 0.4452
44 0.5392 0.9215 0.4608
45 0.4739 0.9479 0.5261
46 0.427 0.8539 0.573
47 0.4574 0.9148 0.5426
48 0.5204 0.9593 0.4796
49 0.5764 0.8472 0.4236
50 0.5427 0.9146 0.4573
51 0.4732 0.9463 0.5268
52 0.4247 0.8494 0.5753
53 0.3564 0.7127 0.6436
54 0.3265 0.653 0.6735
55 0.6081 0.7838 0.3919
56 0.7234 0.5532 0.2766
57 0.7313 0.5373 0.2687
58 0.6996 0.6007 0.3004
59 0.6665 0.6671 0.3335
60 0.5949 0.8101 0.4051
61 0.525 0.9499 0.475
62 0.5055 0.989 0.4945
63 0.4235 0.847 0.5765
64 0.4321 0.8641 0.5679
65 0.553 0.894 0.447
66 0.744 0.512 0.256
67 0.6567 0.6867 0.3433
68 0.5563 0.8873 0.4437
69 0.5346 0.9308 0.4654
70 0.4234 0.8467 0.5766
71 0.3149 0.6298 0.6851
72 0.2147 0.4293 0.7853
73 0.1232 0.2464 0.8768


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level0 0OK
5% type I error level00OK
10% type I error level00OK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 0, df1 = 2, df2 = 74, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 0, df1 = 6, df2 = 70, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 0, df1 = 2, df2 = 74, p-value = 1


Variance Inflation Factors (Multicollinearity)
> vif
StatusDummy  CurryDummy Interaction 
          2           2           3